Research Center for Agricultural Information Technology

Quantitative evaluation of the shapes of biological organs is often required in various research fields, such as agronomy, medicine, genetics, ecology, and taxonomy. Elliptic Fourier descriptors (EFDs), proposed by Kuhl and Giardina (1982), can delineate any type of shape with a closed two-dimensional contour and have been effectively applied to the evaluation of various biological shapes in animals (Bierbaum and Ferson 1986; Diaz et al. 1989; Ferson et al. 1985; Rohlf and Archie 1984) and plants (Furuta et al. 1995; Iwata et al. 1998; McLellan 1993; Ohsawa et al. 1998; White et al. 1988). Quantization of shapes is a prerequisite for evaluating the inheritance of morphological traits in quantitative genetics. There are many reports showing that measurements based on EFDs are helpful for such quantization of the shapes of plant and animal organs. For instance, Iwata et al. (2000) conducted a diallele analysis of the shape of Japanese radish (Raphanus sativus L.) roots, using the principal component scores of the EFDs as shape characteristics. Quantitative trait loci (QTL) analysis has also been conducted using the principal component scores of EFDs concerning the shape of the male genitalia of Drosophila species (Laurie et al. 1997; Liu et al. 1996). The shape evaluation method based on EFDs can be a powerful tool for analyzing biological shapes, but it is not easy for a researcher to use this method because it involves several complex procedures, such as image processing, contour recording, derivation of the descriptors, and multivariate analysis of the descriptors. In this article we present SHAPE, a package of programs for evaluating biological contour shapes based on EFDs. This package contains programs for image processing, contour recording, derivation of EFDs, principal component analysis of EFDs, and visualization of shape variations estimated by the principal components. With the aid of this package, a researcher can easily analyze shapes on a personal computer without special knowledge about the procedures related to the method. The principal component scores obtained by the procedures can be used directly as observed values of shape characteristics for the subsequent analyses. SHAPE is characterized by the following features: (1) The packaged programs are easily operated with the aid of a graphical user interface (GUI); (2) No special computer devices for image processing are required; (3) A large number of samples (say 1,000) can be treated; (4) The scores of principal components are stored in tabbed text format files and can be easily exported for analysis by other software; and (5) The variations in shape accounted for by the principal components can be visualized and printed out.

CO, H 2 , and CH 4 uptake by the soil of an arable field and a forest soil (360 m apart) was measured by a closed‐chamber method in temperate Japan for about 1 year. CO production observed was exponentially dependent on top soil temperature. CO production was greater in the forest soil than in the soil of the arable field at the same soil temperature. (Gross) CO, H 2 , and CH 4 deposition velocities ranged from 0 to 7×10 −2 , from 0 to 9×10 −2 , and from 0.05 to 0.1×10 −2 cm s −1 in the arable field and from 1.5 to 4.5×10 −2 , 5 to 8×10 −2 , and from 0.3 to 0.6×10 −2 cm s −1 in the forest, respectively. Variations in the deposition velocities were smaller in the forest than in the arable field and corresponded to variations in soil moisture in the top soil. Seasonal trends caused by the variation in temperature were observed only for CH 4 deposition, reflecting the clear dependence on soil temperature. Application of dead plant material to the arable field led to acceleration of CO and H 2 deposition onto the soil. The deposition velocities of CO and H 2 were positively correlated ( n =36, R 2* = 0.881, p <0.0001; R 2* is the coefficient of determination adjusted by degrees of freedom) in the arable field and ( n = 37, R 2* = 0.408, p <0.0001) in the forest, suggesting diffusion control on their deposition velocities.

As part of national biosecurity programs, cargo imports, passenger baggage, and international mail are inspected at ports of entry to verify compliance with phytosanitary regulations and to intercept potentially damaging nonnative species to prevent their introduction. Detection of organisms during inspections may also provide crucial information about the species composition and relative arrival rates in invasion pathways that can inform the implementation of other biosecurity practices such as quarantines and surveillance. In most regions, insects are the main taxonomic group encountered during inspections. We gathered insect interception data from nine world regions collected from 1995 to 2019 to compare the composition of species arriving at ports in these regions. Collectively, 8,716 insect species were intercepted in these regions over the last 25 yr, with the combined international data set comprising 1,899,573 interception events, of which 863,972 were identified to species level. Rarefaction analysis indicated that interceptions comprise only a small fraction of species present in invasion pathways. Despite differences in inspection methodologies, as well as differences in the composition of import source regions and imported commodities, we found strong positive correlations in species interception frequencies between regions, particularly within the Hemiptera and Thysanoptera. There were also significant differences in species frequencies among insects intercepted in different regions. Nevertheless, integrating interception data among multiple regions would be valuable for estimating invasion risks for insect species with high likelihoods of introduction as well as for identifying rare but potentially damaging species.

Substantial losses of nitrogen (N) and phosphorus (P) to the environment occur during food production. These emissions of reactive N (Nr) and P have adverse effects on the environment. The life cycle emissions of Nr and P due to resource consumption can be quantified using N and P footprints. In this study, a common framework developed for the purpose of making comparisons was used to examine the food N and P footprints of China, India, and Japan from 1961 to 2013. The footprints increased significantly in China after 1976 (5.4–19.3 kg-N capita−1 yr−1 and 1.20–4.77 kg-P capita−1 yr−1 in 1976–2013) with the higher consumption of meat and vegetables. In India, an increase in milk and vegetable consumption resulted in a gradual increase in the footprints since 1976 (8.5–11.4 kg-N capita−1 yr−1, 0.99–1.6 kg-P capita−1 yr−1 in 1976–2013). In Japan, the footprints increased until 1993 (12.2–28.3 kg-N capita−1 yr−1, 2.59–8.43 kg-P capita−1 yr−1 in 1961–1993) before declining (21.8 kg-N capita−1 yr−1, 6.05 kg-P capita−1 yr−1 in 2013), with a constant increase in meat consumption, a decrease in cereals, and improvements in nutrient use efficiency. The N footprint tends to be more sensitive to the consumption of meat, milk, oil crops, fish, and seafood, and the P footprint tends to be more sensitive to vegetables. By analysing the Asian giants, the key food items to target to reduce the footprints are identified. If the per-capita average footprints in high and middle income countries were the same as that in Japan in 1993, the global food N and P footprints would increase by factors of 1.18–1.89 by 2030. The use of these results with other advances in agriculture practices has the potential to improve nutrient use efficiency and to promote more efficiently-produced food.

The influence of forest operations on forest soil and water continues to be an issue of concern in forest management. Research has focused on evaluating forest operation effects on numerous soil and water quality indicators. However, poorly drained forested watersheds with organic soil surface horizons have not been extensively investigated. A study was initiated in the Tidewater region of North Carolina to gain a better understanding of the impact of harvesting operations on poorly drained organic soils. Soils on the study site, having >80% organic matter (OM) content to a depth of 60 cm below the soil surface, were classified as shallow organic soils. Soil physical properties were examined by collecting soil cores from control and treatment watersheds in a nested design. Compaction caused by the harvest operation increased bulk density (D b ) from 0.22 to 0.27 g cm −3 , decreased saturated hydraulic conductivity ( k sat ) from 397 to 82 cm h −1 , and decreased the drained volume for a given water table depth. However, D b following the harvest remained low at 0.27 g cm −3 The drained volume at equilibrium following the lowering of the water table from the soil surface to a depth of 200 cm was reduced by 10% from that of control watershed as a result of harvesting.

Nitrification in terrestrial soils is one of the major processes of emission of nitrous oxide (N2O), a potent greenhouse gas and stratospheric-ozone-depleting substance. We assessed the fraction of N2O emission associated with nitrification in soil through a meta-analysis and sensitivity analysis using a process-based model. We corrected observational values of gross nitrification and associated N2O emission rates from 71 records for various soils in the world spanning from 0.006% to 29.5%. We obtained a median value of 0.14%, and then assessed how the nitrification-associated N2O emission fraction has been considered in terrestrial nitrogen cycle models. Using a process-based biogeochemical model, we conducted a series of sensitivity analyses for the effects of different values of nitrification-associated N2O emission fraction on soil N2O emission. Using an empirical relationship between soil pH and nitrification-associated N2O emission fraction, the model well simulated global emission patterns (global total in the 2000s, 16.8 Tg N2O yr-1). Differences in the nitrification-associated N2O emission fraction caused differences in total N2O emission of as much as 2.5 Tg N2O yr-1. Therefore, to obtain reliable estimation of soil N2O emission for nitrogen and climate management, it is important to constrain the parameterization in models by ensuring extensive and accurate observations.

Transgenic rice plants overexpressing a mutant rice gene for anthranilate synthase alpha subunit (OASA1D) accumulate large amounts of free tryptophan (Trp) with few adverse effects on the phenotype, except for poor germination and weak seedling growth. Metabolic profiling of 8-d-old seedlings of Nipponbare and two high-Trp lines, HW1 and HW5, by high performance liquid chromatography-photo diode array (HPLC-PDA) confirmed that, relative to Nipponbare, only the peak attributed to Trp was significantly changed in the profiles of the OASA1D lines. More detailed and targeted analysis using HPLC coupled with tandem mass spectrometry revealed that the OASA1D lines had higher levels of anthranilate, tryptamine, and serotonin than Nipponbare, but these metabolites were at much lower levels than free Trp. The levels of phenylalanine (Phe) and tyrosine (Tyr) were not affected by the overproduction of Trp. Transcriptomic analysis by microarray validated by quantitative Real-Time PCR (qRT-PCR) revealed that at least 12 out of 21 500 genes showed significant differential expression among genotypes. Except for the OASA1D transgene and a putative IAA beta-glucosyltransferase, these were not related to Trp metabolism. Most importantly, the overexpression of the OASA1D and the consequent accumulation of Trp in these lines had little effect on the overall transcriptome, consistent with the minimal effects on growth and the metabolome. Integrated analysis of the metabolome and transcriptome of these OASA1D transgenic lines indicates that the over-accumulation of free Trp may be partly due to the low activity of Trp decarboxylase or other metabolic genes that directly utilize Trp as a substrate.

We assessed the genetic diversity in Japanese indigenous common buckwheat (Fagopyrum esculentum) cultivars using amplified fragment length polymorphism (AFLP) and simple sequence repeat (SSR) markers and investigated the relationships between the genetic diversity and agronomic traits. The average expected intracultivar hetero zygosity was 0.303 for AFLP and 0.819 for SSR. The differentiations among agroecotypes, among cultivars within an agroecotype, and among cultivars were small (0.002, 0.024, and 0.026 for SSR and 0.013, 0.013, and 0.026 for AFLP, respectively) but statistically significant from zero except for the SSR differentiation among agroecotypes. In principal coordinates analysis, cultivars within the same agroecotype tended to cluster, indicating that agroecotypes well reflected the genetic relationships among cultivars. In AFLP, the differentiation among the agroecotypes was more distinct than in SSR, and genetic distance showed a moderate correlation with the difference in quantitative traits, indicating that AFLP can resolve the relationships among cultivars with better resolution than SSR. By contrast, SSR may be more sensitive to demographic changes. Four of the five SSR markers showed a significant positive correlation (Kendall's tau = 0.382-0.607) between allelic richness and variation in flowering timing, indicating that cumulative bottleneck events have occurred during the population history, with a decline in the variation of photosensitivity of flowering.

Diabetes is the main chronic disease that greatly affects human life. Up to now, many measures have been taken to cope with the disease, among which natural products with hypoglycemic effects have aroused great interest. The objective of this study was to evaluate the hypoglycemic effects of Morus abla L. cv. longsang 1 leaf-derived water extract in vitro and in vivo. These leaves were firstly subjected to water extraction, and the obtained products were further isolated for polysaccharides, flavonoids and alkaloids. The α-glucosidase activity and anti-protein glycosylation activity of the aqueous extracts were examined in vitro. Hyperglycemic mouse models were used to evaluate the hypoglycemic effects of the aqueous extract by blood biochemical parameters, intestinal microbiota, and pathological changes to the kidneys. The results showed that the main hypoglycemic components in the aqueous extracts were flavonoids and alkaloids and their inhibition rates against α-glucosidase activity were 86.12 ± 1.79% and 87.29 ± 1.32%, respectively. High-dose mulberry leaf water extracts can reduce the blood glucose of diabetic mice by 28.17% and improve glucose tolerance by 19.02%. Furthermore, mulberry leaf water extracts could reduce the serum free fatty acid (FFA), tumor necrosis factor-α (TNF-α), insulin and glycated serum protein content, while alleviating kidney damage and improving intestinal microbiota. These results indicated that the synergistic effects among the different components of mulberry leaves might explain their alleviating effects on diabetic syndrome and thus provide a simple, convenient way to obtain the hypoglycemic components from mulberry leaves.

Variations of leaf form, i.e., differences in shape and size, among citrus varieties and the genotype × environment (GE) interactions influencing the variations were examined. Leaf shape was quantitatively measured by the score of the principal components of elliptic Fourier descriptors (EFDs). Leaf size was measured in terms of area and perimeter. The first four principal components of EFDs, which could explain over 90 % of the shape variations, were good measures of the length to width ratio, the position of the center of gravity, the curvature, and the degree of roundness. Nested ANOVA for the leaf form variations in nine citrus varieties indicated that the variations accounted for by the 1st, 2nd and 4th components were inherited. GE interaction of the leaf form was investigated using the data appertaining to seven genotypes from eight locations; the interaction was significant for all the principal components examined except the third. Although the interaction fitted very poorly to a joint linear regression analysis model developed from the data, it was effectively explained by an additive main effect and multiplicative interaction model where the score of the interaction principal component was highly correlated with the stability indices. Our results suggest that the genotype was the main source of variation in leaf shape, but not in size, and that the contribution of GE interaction was minor to both shape and size, although statistically significant at the 1 % probability level.

Abstract To improve several agronomic traits in crisphead lettuce ( Lactuca sativa L.) under high-temperature growth conditions, we investigated the correlation among those traits in multiple cultivars and performed genetic mapping of their causal genes. In a field cultivation test of Empire type (serrated leaf) and Salinas type (wavy leaf) cultivars, Empire type cultivars showed increased tipburn susceptibility and late bolting compared with Salinas type cultivars. We attempted genetic mapping of leaf shape and bolting time by ddRAD-seq using the F 2 population derived from a cross between ‘VI185’ (Empire type) and ‘ShinanoGreen’ (Salinas type). These analyses suggested that both traits are controlled by a single locus in LG5. Genotyping of 51 commercial lettuce cultivars with a tightly linked marker ( LG5_v8_252.743Mbp ) at this locus showed an association between its genotype and the serrated leaf phenotype. By further fine mapping and transcriptome analysis, a gene encoding putative CIN-like TCP transcription factor was determined to be a candidate gene at this locus and was designated as LsTCP4 . An insertion of retrotransposable element was found in the allele of ‘VI185’, and its transcript level in the leaves was lower than that in ‘ShinanoGreen’. Because shapes of leaf epidermal cells in ‘VI185’ were similar to those in the TCP family mutant of Arabidopsis thaliana , the leaf shape phenotype was likely caused by reduced expression of LsTCP4 . Furthermore, because it is known that the TCP family protein also controls flowering time via interaction with FT in A. thaliana , it was highly possible that LsTCP4 gave pleiotropic effects on both leaf shape and bolting time in lettuce.

The white-backed planthopper, Sogatella furcifera, and the brown planthopper, Nilaparvata lugens, are pests of rice and migrate from south China to Japan in the rainy season of early summer. In order to achieve high-precision migration prediction, a real-time prediction system was developed. In this system, the latest meteorological data are supplied online to an advanced numerical weather prediction model, MM5. The model forecasts three-dimensional atmospheric fields at one-hour intervals. In these fields, a planthopper migration simulation model, GEARN, calculates movement of a number of modeled planthoppers and predicts their relative aerial density at three-hour intervals. The results are converted to maps and become available on the Internet. The maps of relative aerial density provide information about the timing and area of migrations over the next two days. During the main migration season in June and July 2003, the system achieved a prediction quality that was comparable to that of rainfall forecasts by the Japanese Meteorological Agency.

Herein, we performed RNA-seq analysis of ten major tissues/subparts of silkworm larvae. The sequences were mapped onto the reference genome assembly and the reference transcriptome data were successfully constructed. The reference data provided a nearly complete sequence for sericin-1, a major silk gene with a complex structure. We also markedly improved the gene model for other genes. The transcriptomic expression was investigated in each tissue and a number of transcripts were identified that were exclusively expressed in tissues such as the testis. Transcripts strongly expressed in the midgut formed tight genomic clusters, suggesting that they originated from tandem gene duplication. Transcriptional factor genes expressed in specific tissues or the silk gland subparts were also identified. We successfully constructed reference transcriptome data in the silkworm and found that a number of transcripts showed unique expression profiles. These results will facilitate basic studies on the silkworm and accelerate its applications, which will contribute to further advances in lepidopteran and entomological research as well as the practical use of these insects.

Enhancing crop yield response to elevated CO2 concentrations (E-[CO2]) is an important adaptation measure to climate change. A high-yielding indica rice cultivar ‘Takanari’ has recently been identified as a potential candidate for high productivity in E-[CO2] resulting fromowing to its large sink and source capacities. To fully utilize these traits, nitrogen should play a major role, but it is unknown how N levels influence the yield response of Takanari to E-[CO2]. We therefore compared grain yield and quality of Takanari with those of Koshihikari, a standard japonica cultivar, in response to Free-Air CO2 enrichment (FACE, +200 μmol mol-1) under three N levels (0, 8, and 12 g m-2) over three seasons. The biomass of both cultivars increased under E-[CO2] at all N levels; however, the harvest index decreased under E-[CO2] in the N- limited treatment for Koshihikari but not for Takanari. The decreased harvest index of Koshihikari resulted from limited enhancement of spikelet number under N- limitation. In contrast, spikelet number increased in E-[CO2] in Takanari even without N application, resulting in significant yield enhancement, averaging 18% over 3 years, whereas Koshihikari exhibited virtually no increase in yield in E-[CO2] under the N- limited condition. Grain appearance quality of Koshihikari was severely reduced by E-[CO2], most notably in N- limited and hot conditions, by a substantial increase in chalky grain, but chalky grain % did not increase in E-[CO2] even without N fertilizer. These results indicated that Takanari could retain its high yield advantage over Koshihikari with limited increase in chalkiness even under limited N conditions and that it could be a useful genetic resource for improving N use efficiency under E-[CO2].

Thousands of insect species have been introduced outside of their native ranges, and some of them strongly impact ecosystems and human societies. Because a large fraction of insects feed on or are associated with plants, nonnative plants provide habitat and resources for invading insects, thereby facilitating their establishment. Furthermore, plant imports represent one of the main pathways for accidental nonnative insect introductions. Here, we tested the hypothesis that plant invasions precede and promote insect invasions. We found that geographical variation in current nonnative insect flows was best explained by nonnative plant flows dating back to 1900 rather than by more recent plant flows. Interestingly, nonnative plant flows were a better predictor of insect invasions than potentially confounding socioeconomic variables. Based on the observed time lag between plant and insect invasions, we estimated that the global insect invasion debt consists of 3,442 region-level introductions, representing a potential increase of 35% of insect invasions. This debt was most important in the Afrotropics, the Neotropics, and Indomalaya, where we expect a 10 to 20-fold increase in discoveries of new nonnative insect species. Overall, our results highlight the strong link between plant and insect invasions and show that limiting the spread of nonnative plants might be key to preventing future invasions of both plants and insects.

Abstract Monitoring plant diseases is essential for farmers to secure crop quantity and quality. Deep learning has recently been applied to plant disease recognition to help farmers take prompt and proper actions to prevent reductions in crop quantity and quality. Generally, deep learning requires a large‐scale dataset with supervised information annotated often by specialists. However, because collecting plant disease images in natural environments is difficult and obtaining proper annotations from specialists is costly, deep learning is infeasible for plant disease recognition tasks. Few‐shot learning (FSL) is an alternative for plant disease recognition using prior knowledge. Although FSL has attracted considerable attention, comprehensive reports on the application of FSL methods for plant disease recognition are required. Here, we introduce FSL with its applications in plant disease recognition. We begin with an overview of computer vision tasks using machine learning and FSL. We provide practical examples of FSL applications. Utilizing these practical examples, we describe different approaches for data augmentation and FSL methods of embedding, multitask learning, transfer learning, and meta‐learning. Further, we summarize how models are optimized for performance with reference to existing studies. Finally, the advantages and disadvantages are discussed, along with potential challenges for FSL applications in plant disease recognition.

So far, only five microsatellite markers have been developed in common buckwheat (Fagopyrum esculentum). The purpose of the present study was to develop a larger number of microsatellite markers in common buckwheat. By sequencing 2785 clones from the libraries, which were enriched for (CT)n and (GT)n repeats using magnetic particles, it was shown that 1483 clones contained microsatellites, of which 352 had unique sequences. Primer pairs were designed for 237 of the microsatellite loci, of which 180 primer pairs each amplified PCR products. Fifty-four primer pairs that each amplified a clear PCR product of the expected size were evaluated for their ability to detect variations in common buckwheat populations and to be utilized in seven related Fagopyrum species. Forty-eight (88.9%) out of the 54 microsatellite markers tested were found to be highly variable (the average number of alleles was 12.2 and the average polymorphism information content (PIC) was 0.79) in a population of cultivated buckwheat. This PIC value was comparatively large when compared with the average values for microsatellite markers reported for other crops. A high rate of successful amplification of common buckwheat microsatellite markers was observed in closely related species; in particular all the 54 loci were successfully amplified in the wild ancestor of cultivated common buckwheat. The microsatellite markers developed in the present study should contribute to the promotion of molecular breeding in common buckwheat.

BACKGROUND: Understanding mechanisms of sugar accumulation and composition is essential to determining fruit quality and maintaining a desirable balance of sugars in plant storage organs. The major sugars in mature Rosaceae fruits are sucrose, fructose, glucose, and sorbitol. Among these, sucrose and fructose have high sweetness, whereas glucose and sorbitol have low sweetness. Japanese pear has extensive variation in individual sugar contents in mature fruit. Increasing total sugar content and that of individual high-sweetness sugars is a major target of breeding programs. The objective of this study was to identify quantitative trait loci (QTLs) associated with fruit traits including individual sugar accumulation, to infer the candidate genes underlying the QTLs, and to assess the potential of genomic selection for breeding pear fruit traits. RESULTS: We evaluated 10 fruit traits and conducted genome-wide association studies (GWAS) for 106 cultivars and 17 breeding populations (1112 F1 individuals) using 3484 tag single-nucleotide polymorphisms (SNPs). By implementing a mixed linear model and a Bayesian multiple-QTL model in GWAS, 56 SNPs associated with fruit traits were identified. In particular, a SNP located close to acid invertase gene PPAIV3 on chromosome 7 and a newly identified SNP on chromosome 11 had quite large effects on accumulation of sucrose and glucose, respectively. We used 'Golden Delicious' doubled haploid 13 (GDDH13), an apple reference genome, to infer the candidate genes for the identified SNPs. In the region flanking the SNP on chromosome 11, there is a tandem repeat of early responsive to dehydration (ERD6)-like sugar transporter genes that might play a role in the phenotypes observed. CONCLUSIONS: SNPs associated with individual sugar accumulation were newly identified at several loci, and candidate genes underlying QTLs were inferred using advanced apple genome information. The candidate genes for the QTLs are conserved across Pyrinae genomes, which will be useful for further fruit quality studies in Rosaceae. The accuracies of genomic selection for sucrose, fructose, and glucose with genomic best linear unbiased prediction (GBLUP) were relatively high (0.67-0.75), suggesting that it would be possible to select individuals having high-sweetness fruit with high sucrose and fructose contents and low glucose content.

Ninety-nine accessions of melon (Cucumis melo L.) mainly from East and South Asia were analyzed based on the polymorphism of 210 amplified fragment length polymorphism (AFLP) bands to reveal the genetic structure and phylogenetic relationship in Asian melon. A cluster analysis based on their genetic similarity revealed three major clusters, i.e., a vars. makuwa and conomon group, a small-seed type group and a group of Japanese F1 cultivars and large-seed type accessions. Most of the East Asian melon accessions classified into the first group were of the small-seed type with a seed length shorter than 9.0 mm. The varieties of C. melo were roughly divided into two groups by a principal co-ordinate analysis based on AFLP data, that is, the group of vars. makuwa and conomon and small-seed type melon and the group of var. reticulatus and large-seed type melon. Indian melon accessions were rich in genetic variation. Melon accessions closely related to vars. makuwa and conomon were found in east India, and they were considered as possible candidates of the prototype of vars. makuwa and conomon.

Sorghum [Sorghum bicolor (L.) Moench] grown locally by Japanese farmers is generically termed Takakibi, although its genetic diversity compared with geographically distant varieties or even within Takakibi lines remains unclear. To explore the genomic diversity and genetic traits controlling biomass and other physiological traits in Takakibi, we focused on a landrace, NOG, in this study. Admixture analysis of 460 sorghum accessions revealed that NOG belonged to the subgroup that represented Asian sorghums, and it was only distantly related to American/African accessions including BTx623. In an attempt to dissect major traits related to biomass, we generated a recombinant inbred line (RIL) from a cross between BTx623 and NOG, and we constructed a high-density linkage map based on 3,710 single-nucleotide polymorphisms obtained by restriction-site-associated DNA sequencing of 213 RIL individuals. Consequently, 13 fine quantitative trait loci (QTLs) were detected on chromosomes 2, 3, 6, 7, 8 and 9, which included five QTLs for days to heading, three for plant height (PH) and total shoot fresh weight and two for Brix. Furthermore, we identified two dominant loci for PH as being identical to the previously reported dw1 and dw3. Together, these results corroborate the diversified genome of Japanese Takakibi, while the RIL population and high-density linkage map generated in this study will be useful for dissecting other important traits in sorghum.